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Q:
Let zbe a normal random variable with mean 0 and standard deviation 1. What is P(z> -1.1)?
a) 0.36432
b) 0.8643
c) 0.1357
d) -0.1357
e) -0.8643
Q:
Let zbe a normal random variable with mean 0 and standard deviation 1. What is P(z< -2.1)?
a) 0.4821
b) -0.4821
c) 0.9821
d) 0.0179
e) -0.0179
Q:
Let zbe a normal random variable with mean 0 and standard deviation 1. What is P(z> 2.4)?
a) 0.4918
b) 0.9918
c) 0.0082
d) 0.4793
e) 0.0820
Q:
Let zbe a normal random variable with mean 0 and standard deviation 1. What is P(1.3 < z< 2.3)?
a) 0.4032
b) 0.9032
c) 0.4893
d) 0.0861
e) 0.0086
Q:
Let zbe a normal random variable with mean 0 and standard deviation 1. What is P(z< 1.3)?
a) 0.4032
b) 0.9032
c) 0.0968
d) 0.3485
e) 0. 5485
Q:
A standard normal distribution has the following characteristics:
a) the mean and the variance are both equal to 1
b) the mean and the variance are both equal to 0
c) the mean is equal to the variance
d) the mean is equal to 0 and the variance is equal to 1
e) the mean is equal to the standard deviation
Q:
The area to the left of the mean in any normal distribution is equal to _______.
a) the mean
b) 1
c) the variance
d) 0.5
e) -0.5
Q:
The total area underneath any normal curve is equal to _______.
a) the mean
b) one
c) the variance
d) the coefficient of variation
e) the standard deviation
Q:
The normal distribution is an example of _______.
a) a discrete distribution
b) a continuous distribution
c) a bimodal distribution
d) an exponential distribution
e) a binomial distribution
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job will be completed 24 minutes or more, i.e., P(x 24) is __________________.
a) 0.100
b) 0.000
c) 0.333
d) 0.600
e) 1.000
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job is completed in less than or equal to 22 minutes, i.e., P(x 22) is __________________.
a) 0.200
b) 0.300
c) 0.000
d) 0.250
e) 1.000
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job is completed in less than 17 minutes, i.e., P(x< 17) is __________________.
a) 0.500
b) 0.300
c) 0.000
d) 0.250
e) 1.000
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job is completed in 33 to 35 minutes, inclusively, i.e., P(33 x 35) is __________________.
a) 0.5080
b) 0.000
c) 0.375
d) 0.200
e) 1.000
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job is completed in 21.75 to 24.25 minutes, inclusively, i.e., P(21.75 x 24.25) is __________________.
a) 0.250
b) 0.333
c) 0.375
d) 0.000
e) 1.000
Q:
If x, the time (in minutes) to complete an change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the probability that an oil change job is completed in 25 to 28 minutes, inclusively, i.e., P(25 x 28) is __________________.
a) 0.250
b) 0.500
c) 0.300
d) 0.750
e) 81.000
Q:
If x, the time (in minutes) to complete an oil change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the standard deviation of this distribution is __________________.
a) unknown
b) 8.33
c) 0.833
d) 2.89
e) 1.89
Q:
If x, the time (in minutes) to complete an oil change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the mean of this distribution is __________________.
a) 50
b) 25
c) 10
d) 15
e) 5
Q:
If x, the time (in minutes) to complete an oil change job at certain auto service station, is uniformly distributed over the interval 20 to 30, inclusively (20 x 30), then the height of this distribution, f(x), is __________________.
a) 1/10
b) 1/20
c) 1/30
d) 12/50
e) 1/60
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then P(x 10) is __________________.
a) 0.750
b) 0.000
c) 0.333
d) 0.500
e) 0.900
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then P(x 11) is __________________.
a) 0.750
b) 0.000
c) 0.333
d) 0.500
e) 1.000
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then P(x< 7) is __________________.
a) 0.500
b) 0.000
c) 0.375
d) 0.250
e) 1.000
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then the probability, P(13 x 15), is __________________.
a) 0.250
b) 0.500
c) 0.375
d) 0.000
e) 1.000
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then the probability, P(10.0 x 11.5), is __________________.
a) 0.250
b) 0.333
c) 0.375
d) 0.500
e) 0.750
Q:
If xis uniformly distributed over the interval 8 to 12, inclusively (8 x 12), then the probability, P(9 x 11), is __________________.
a) 0.250
b) 0.500
c) 0.333
d) 0.750
e) 1.000
Q:
If the number of parking spots at urban grocery stores is uniformly distributed over the interval 90 to 140, inclusively (90 x 140), then P(x= exactly 100) is __________________.
a) 0.750
b) 0.000
c) 0.333
d) 0.500
e) 0.900
Q:
If the number of parking spots at urban grocery stores is uniformly distributed over the interval 90 to 140, inclusively (90 x 140), then the standard deviation of this distribution is __________________.
a) 4.16
b) 50
c) 14.4
d) 7.07
e) 28.2
Q:
If the number of parking spots at urban grocery stores is uniformly distributed over the interval 90 to 140, inclusively (90 x 140), inclusively (90 x 140), then the mean of this distribution is __________________.
a) 115
b) 230
c) 45
d) 70
e) unknown
Q:
Suppose the number of parking spots at urban grocery stores is uniformly distributed over the interval 90 to 140, inclusively (90 x 140), then the height of this distribution, f(x), is __________________.
a) 1/90
b) 1/50
c) 1/140
d) 1/200
e) 1/500
Q:
For an exponential distribution, the mean and the median are equal.
Q:
For an exponential distribution, the mean is always equal to its variance.
Q:
If arrivals at a bank followed a Poisson distribution, then the time between arrivals would follow a binomial distribution.
Q:
A correction for continuity must be made when approximating the binomial distribution problems using a normal distribution.
Q:
Binomial distributions in which the sample sizes are large may be approximated by a Poisson distribution.
Q:
The normal approximation for binomial distribution can be used when n=10 and p=1/5.
Q:
The area under the standard normal distribution between 0 and 2 is twice the area between 0 and 1.
Q:
The area under the standard normal distribution between -1 and 1 is twice the area between 0 and 1.
Q:
In a standard normal distribution, if the area under curve to the right of a z-value is 0.10, then the area to the left of the same z-value is -0.10.
Q:
The standard normal distribution is also called a finite distribution because its mean is zero and standard deviation one, always.
Q:
A standard normal distribution has a mean of one and a standard deviation of three.
Q:
A normal distribution with a mean of zero and a standard deviation of 1 is called a null distribution.
Q:
A z-score is the number of standard deviations that a value of a random variable is above or below the mean.
Q:
Since a normal distribution curve extends from minus infinity to plus infinity, the area under the curve is infinity.
Q:
Normal distribution is a symmetrical distribution with its tails extending to infinity on either side of the mean.
Q:
Many human characteristics such as height and weight and many measurements such as variables such as household insurance and cost per square foot of rental space are normally distributed.
Q:
The area of the rectangle depicting a uniform distribution is always equal to the mean of the distribution.
Q:
The height of the rectangle depicting a uniform distribution is the probability of each outcome and it same for all of the possible outcomes
Q:
A uniform continuous distribution is also referred to as a rectangular distribution.
Q:
One hundred policyholders file claims with CareFree Insurance. Ten of these claims are fraudulent. Claims manager Earl Evans randomly selects four of the one hundred claims for thorough investigation. If x represents the number of fraudulent claims in Earl's sample, x has a _______________.
a) normal distribution
b) hypergeometric distribution, but may be approximated by a binomial
c) binomial distribution, but may be approximated by a normal
d) binomial distribution, but may be approximated by a Poisson
e) exponential distribution
Q:
One hundred policyholders file claims with CareFree Insurance. Ten of these claims are fraudulent. Claims manager Earl Evans randomly selects four of the one hundred claims for thorough investigation. If x represents the number of fraudulent claims in Earl's sample, x has a _______________ distribution.
a) continuous
b) normal
c) binomial
d) hypergeometric
e) exponential
Q:
If sampling is performed without replacement, the hypergeometric distribution should be used. However, the binomial may be used to approximate this if _______.
a) n > 5%N
b) n < 5%N
c) the population size is very small
d) there are more than two possible outcomes of each trial
e) the outcomes are continuous
Q:
Ten policyholders file claims with CareFree Insurance. Three of these claims are fraudulent. Claims manager Earl Evans randomly selects three of the ten claims for thorough investigation. If x represents the number of fraudulent claims in Earl's sample, P(x=1) is _______________.
a) 0.5250
b) 0.4410
c) 0.3000
d) 0.6957
e) 0.9957
Q:
Ten policyholders file claims with CareFree Insurance. Three of these claims are fraudulent. Claims manager Earl Evans randomly selects three of the ten claims for thorough investigation. If x represents the number of fraudulent claims in Earl's sample, P(x=0) is _______________.
a) 0.0083
b) 0.3430
c) 0.0000
d) 0.2917
e) 0.8917
Q:
Circuit boards for wireless telephones are etched, in an acid bath, in batches of 100 boards. A sample of seven boards is randomly selected from each lot for inspection. A particular batch contains two defective boards; and x is the number of defective boards in the sample. P(x=0) is _______.
a) 0.1315
b) 0.8642
c) 0.0042
d) 0.6134
e) 0.8134
Q:
Circuit boards for wireless telephones are etched, in an acid bath, in batches of 100 boards. A sample of seven boards is randomly selected from each lot for inspection. A particular batch contains two defective boards; and x is the number of defective boards in the sample. P(x=2) is _______.
a) 0.1315
b) 0.8642
c) 0.0042
d) 0.6134
e) 0.0034
Q:
Circuit boards for wireless telephones are etched, in an acid bath, in batches of 100 boards. A sample of seven boards is randomly selected from each lot for inspection. A batch contains two defective boards; and x is the number of defective boards in the sample. P(x=1) is _______.
a) 0.1315
b) 0.8642
c) 0.0042
d) 0.6134
e) 0.6789
Q:
Aluminum castings are processed in lots of five each. A sample of two castings is randomly selected from each lot for inspection. A particular lot contains one defective casting; and x is the number of defective castings in the sample. P(x=1) is _______.
a) 0.2
b) 0.4
c) 0.6
d) 0.8
e) 1.0
Q:
Aluminum castings are processed in lots of five each. A sample of two castings is randomly selected from each lot for inspection. A particular lot contains one defective casting; and x is the number of defective castings in the sample. P(x=0) is _______.
a) 0.2
b) 0.4
c) 0.6
d) 0.8
e) 1.0
Q:
Suppose an interdisciplinary committee of 3 faculty members is to be selected from a group consisting of 4 men and 5 women. The probability that one male faculty and two female faculty are selected is approximately ______
a) 0.15
b) 0.06
c) 0.33
d) 0.48
e) 0.58
Q:
Suppose an interdisciplinary committee of 3 faculty members is to be selected from a group consisting of 4 men and 5 women. The probability that all three faculty selected are men is approximately _______
a) 0.05
b) 0.33
c) 0.11
d) 0.80
e) 0.90
Q:
The probability of selecting 3 female employees and 7 male employees to win a promotional trip a company with 10 female and 50 male employees would best be modeled with the _______.
a) binomial distribution
b) hypergeometric distribution
c) Poisson distribution
d) hyperbinomial distribution
e) exponential distribution
Q:
The probability of selecting 2 baseball players and 3 basketball players for an intermural competition at a small sports camp would best be modeled with the _______.
a) binomial distribution
b) hypergeometric distribution
c) Poisson distribution
d) hyperbinomial distribution
e) exponential distribution
Q:
The hypergeometric distribution must be used instead of the binomial distribution when ______
a) sampling is done with replacement
b) sampling is done without replacement
c) n≥5% N
d) both b and c
e) there are more than two possible outcomes
Q:
Which of the following conditions is not a condition for the hypergeometric distribution?
a) the probability of success is the same on each trial
b) sampling is done without replacement
c) there are only two possible outcomes
d) trials are dependent
e) n < 5%N
Q:
The number of defects per 1,000 feet of extruded plastic pipe is best modeled with the ________________.
a) Poisson distribution
b) Pascal distribution
c) binomial distribution
d) hypergeometric distribution
e) exponential distribution
Q:
The number of bags arriving on the baggage claim conveyor belt in a 3 minute time period would best be modeled with the _________.
a) binomial distribution
b) hypergeometric distribution
c) Poisson distribution
d) hyperbinomial distribution
e) exponential distribution
Q:
The Poisson distribution is being used to approximate a binomial distribution. Ifn=60 andp=0.02, what value of lambda would be used?
a) 0.02
b) 12
c) 0.12
d) 1.2
e) 120
Q:
The Poisson distribution is being used to approximate a binomial distribution. Ifn=30 andp=0.03, what value of lambda would be used?
a) 0.09
b) 9.0
c) 0.90
d) 90
e) 30
Q:
On Monday mornings, customers arrive at the coffee shop drive thru at the rate of 6 cars per fifteen minute interval. Using the Poisson distribution, the probability that five cars will arrive during the next five minute interval is _____________.
a) 0.1008
b) 0.0361
c) 0.1339
d) 0.1606
e) 0.3610
Q:
On Monday mornings, customers arrive at the coffee shop drive thru at the rate of 6 cars per fifteen-minute interval. Using the Poisson distribution, the probability that five cars will arrive during the next fifteen-minute interval is _____________.
a) 0.1008
b) 0.0361
c) 0.1339
d) 0.1606
e) 0.5000
Q:
Assume that a random variable has a Poisson distribution with a mean of 5 occurrences per ten minutes. The number of occurrences per hour follows a Poisson distribution with λ equal to _________
a) 5
b) 60
c) 30
d) 10
e) 20
Q:
The number of cars arriving at a toll booth in five-minute intervals is Poisson distributed with a mean of 3 cars arriving in five-minute time intervals. The probability of 3 cars arriving over a five-minute interval is _______.
a) 0.2700
b) 0.0498
c) 0.2240
d) 0.0001
e) 0.0020
Q:
The number of cars arriving at a toll booth in five-minute intervals is Poisson distributed with a mean of 3 cars arriving in five-minute time intervals. The probability of 5 cars arriving over a five-minute interval is _______.
a) 0.0940
b) 0.0417
c) 0.1500
d) 0.1008
e) 0.2890
Q:
It is known that screws produced by a certain company will be defective with probability .01 independently of each other. The company sells the screws in packages of 25 and offers a money-back guarantee that at most 1 of the 25 screws is defective. Using Poisson approximation for binomial distribution, the probability that the company must replace a package is approximately _________
a) 0.01
b) 0.1947
c) 0.7788
d) 0.0264
e) 0.2211
Q:
In a certain communications system, there is an average of 1 transmission error per 10 seconds. Assume that the distribution of transmission errors is Poisson. The probability of 1 error in a period of one-half minute is approximately ________
a) 0.1493
b) 0.3333
c) 0.3678
d) 0.1336
e) 0.03
Q:
A large industrial firm allows a discount on any invoice that is paid within 30 days. Of all invoices, 10% receive the discount. In a company audit, 15 invoices are sampled at random. The mean (average) value of the number of the 15 sampled invoices that receive discount is _______
a) 1
b) 3
c) 1.5
d) 2
e) 10
Q:
A large industrial firm allows a discount on any invoice that is paid within 30 days. Of all invoices, 10% receive the discount. In a company audit, 10 invoices are sampled at random. The probability that fewer than 3 of the 10 sampled invoices receive the discount is approximately_______________.
a) 0.1937
b) 0.057
c) 0.001
d) 0.3486
e) 0.9298
Q:
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail order business, but after scanning the list she doubts the authenticity of the list. She randomly selects five names from the list for validation. If 40% of the names on the list are non-authentic, and x is the number on non-authentic names in her sample, the expected (average) value of x is ______________.
a) 2.50
b) 2.00
c) 1.50
d) 1.25
e) 1.35
Q:
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail order business, but after scanning the list she doubts the authenticity of the list. She randomly selects five names from the list for validation. If 40% of the names on the list are non-authentic, and x is the number of non-authentic names in her sample, P(x>0) is ______________.
a) 0.2172
b) 0.9533
c) 0.1846
d) 0.9222
e) 1.0000
Q:
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail order business, but after scanning the list she doubts the authenticity of the list. She randomly selects five names from the list for validation. If 40% of the names on the list are non-authentic, and x is the number of non-authentic names in her sample, P(x<2) is ______________.
a) 0.3370
b) 0.9853
c) 0.9785
d) 0.2333
e) 0.5000
Q:
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail order business, but after scanning the list she doubts the authenticity of the list. She randomly selects five names from the list for validation. If 40% of the names on the list are non-authentic, and x is the number of non-authentic names in her sample, P(x=0) is ______________.
a) 0.8154
b) 0.0467
c) 0.0778
d) 0.4000
e) 0.5000